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Christopher T. Lowenkamp
Researcher at University of Missouri–Kansas City
Publications - 85
Citations - 4670
Christopher T. Lowenkamp is an academic researcher from University of Missouri–Kansas City. The author has contributed to research in topics: Recidivism & Risk assessment. The author has an hindex of 33, co-authored 83 publications receiving 4108 citations. Previous affiliations of Christopher T. Lowenkamp include University of Cincinnati & Government of the United States of America.
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Risk, race, and recidivism: predictive bias and disparate impact*
TL;DR: The authors examined the relationship among race, risk assessment [the Post Conviction Risk Assessment (PCRA), and future arrest, and found that most (66 percent) of the racial difference in PCRA scores is attributable to criminal history.
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Risk/Need Assessment, Offender Classification, and the Role of Childhood Abuse
TL;DR: Analyses indicated that the LSI-R is a valid (predictive) instrument for this sample of female offenders and that a history of prior abuse fails to add to the prediction of reincarceration, once risk is controlled for using the L SI-R.
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Applying the Risk Principle to Sex Offenders Can Treatment Make Some Sex Offenders Worse
TL;DR: In this article, the effects of different levels of treatment intensity on 238 sexual offenders who are on parole were explored and the findings suggest that the risk principle does, in fact, apply to sexual offenders.
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Exploring the validity of the Level of Service Inventory-Revised with Native American offenders.
TL;DR: In this paper, the predictive validity of the Level of Service Inventory-Revised (LOSI) was evaluated using a sample of Native American and White offenders in a northern midwestern state.
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Predicting outcome with the Level of Service Inventory-Revised: The importance of implementation integrity
TL;DR: The Level of Service Inventory-Revised (LSI-R) is a risk/need assessment instrument that was designed to assist correctional agencies in classifying offenders based upon risk of re-offending, thereby allowing agencies to assign appropriate levels of risk and develop intervention/case-plans accordingly as mentioned in this paper.